LifeKit Predict analyzes a patient’s genetic makeup and says it can determine how likely they are to become addicted to opioids–before they’re even prescribed painkillers.

A familiar narrative of the opioid crisis that’s been raging in the U.S. for nearly a decade goes something like this: A patient comes to the hospital seeking treatment and relief from the pain of a recent injury (in many well-known stories, this patient is a student athlete). Their issue is addressed, and they’re prescribed something to manage the pain–often OxyContin or Vicodin.

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The drugs dull the pain, but once the pain is gone, a subset of patients keep popping the pills, not out of necessity, but because they’ve become dependent on them. These commonly prescribed painkillers are opioids, and produce a euphoric high that mirrors the sensation of their illegal counterparts, heroin and fentanyl, which patients often turn to after their prescriptions run out. Opioid overdoses are now the most common cause of death in Americans under the age of 50; 64,000 people died from the drugs last year alone.

[Photo: courtesy Prescient Medicine]Why some of the patients become addicted to opioid painkillers has remained somewhat of a mystery; prescribing them, consequently, is a gamble. A new test from Prescient Medicine, a predictive health and analytics company, aims to de-risk the prescription of opioid painkillers by using genetic testing to determine the likelihood that a patient will become addicted before they are given the medication. Called LifeKit Predict, the test, according to Prescient, can determine with 97% sensitivity whether an individual will become dependent on opioids, and will enable doctors to opt for a non-opioid treatment course instead.

Prescient, so far, claims that around 10% to 20% of the population demonstrates a gene composition that indicates a greater capacity for addiction. Currently, the company is working with several health practitioner partners to figure out how best to integrate the test into the diagnosis and treatment workflow; they’re running five pilot projects with LifeKit across the country.

Work on LifeKit Predict, says Prescient CEO and medical director Keri Donaldson, began around six years ago. “Our preliminary research set out to ask the pretty basic question: Why do some patients develop drug dependencies and substance-abuse disorders, and others do not?” he says. “There are hundreds of articles about how genes may affect different portions of the addiction cycle–whether that be positive reinforcement, like you take a pill and it feels good, or negative reinforcement, as in you feel sick and take a pill to feel better,” Donaldson says.

[Photo: courtesy Prescient Medicine]Prescient started by researching the potential addictive properties of 10,000 genes–around one-third of the human genome. Over the years, they whittled the list down to 16 genes and their variants (alleles) particularly involved with drug metabolism and brain reward pathways. (This is what physicians are referring to when they describe how certain parts of the brain “light up” in response to stimulation.) In a recent paper published in the Annals of Clinical and Laboratory Science, Prescient described analyzing how these particular 16 genes appeared in 37 patients with a history of opioid addiction; they matched those samples with 16 random control samples to get a sense of the variance in the composition and prevalence of the genes. From that initial sample, Prescient developed the LifeKit algorithm, which scores a patient out of 100, with anything over 52 representing an elevated risk of addiction.

Prescient tested the model on another 138 samples before finalizing the algorithm to ensure that the results from the first small study applied to a larger population.

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Ensuring wider applicability is necessary, especially in the often-fraught field of predictive medicine. Proove Biosciences launched a similar genetic test to determine addiction capacity in 2011. Last year, it went through a leadership change amid allegations of shaky scientific methods; its test was similar to Prescient’s, but combined some non-genetic related questions. While the founder of Proove maintains its legitimacy, and the company is in the process of restructuring, some questions remain in the scientific field as to the validity of its methods.

While experts like Sarah Nelson, associate director of research at the Cambridge Health Alliance Division on Addiction, also caution against taking Prescient’s accuracy claims at face value (fewer than 200 people is a very small sample size), the Prescient test differs from Proove’s in that it algorithmically assesses all of the genes together to create a score. Proove’s highlighted only certain gene mutations that could indicate addiction, but didn’t account for the all of the genetic ensemble. While Prescient is in talks with healthcare providers to bring its test to market, it would benefit the company and give providers peace of mind regarding the accuracy of the test if they could expand their sample size out to somewhere in the thousands to ensure broad applicability.

Predictive tests in the addiction and pain-management spheres are still in their infancy; it will likely take some time to fine-tune the method to the point where it becomes surefire (if that is ever even possible). But, Donaldson says, we’ve long overshot the time for considering a patient’s addiction outcomes before prescribing an opioid. Around one in five patients that walk into doctors’ offices in pain are prescribed the drugs, which are highly effective and efficient, but can have repercussions that are now impossible to ignore. “What the LifeKit test can offer is a holistic picture of risk and benefit of these drugs,” Donaldson says. If the risk is too high, he adds, the doctor should investigate alternative treatments–anything from acupuncture to medical marijuana to nonaddictive drugs, which historically have not been as effective at pain management as opioids, but are improving. “We want to stop highly susceptible patients from having the exposure that may lead them to an addiction and a devastating life ahead,” Donaldson says.

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About the author

Eillie Anzilotti is an assistant editor for Fast Company's Ideas section, covering sustainability, social good, and alternative economies. Previously, she wrote for CityLab.